vllm - ✅(Solved) Fix [Bug]: IndexError when `--renderer-num-workers` + `--mm-processor-cache-type shm` [1 pull requests, 4 comments, 3 participants]

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vllm-project/vllm#38375Fetched 2026-04-08 01:41:49
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Error Message

============================== System Info

OS : Ubuntu 24.04.3 LTS (x86_64) GCC version : (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 Clang version : Could not collect CMake version : Could not collect Libc version : glibc-2.39

============================== PyTorch Info

PyTorch version : 2.10.0+cu129 Is debug build : False CUDA used to build PyTorch : 12.9 ROCM used to build PyTorch : N/A

============================== Python Environment

Python version : 3.12.3 (main, Nov 6 2025, 13:44:16) [GCC 13.3.0] (64-bit runtime) Python platform : Linux-5.14.0-284.118.1.el9_2.x86_64-x86_64-with-glibc2.39

============================== CUDA / GPU Info

Is CUDA available : True CUDA runtime version : 12.9.86 CUDA_MODULE_LOADING set to : GPU models and configuration : GPU 0: NVIDIA H100 80GB HBM3 GPU 1: NVIDIA H100 80GB HBM3 GPU 2: NVIDIA H100 80GB HBM3 GPU 3: NVIDIA H100 80GB HBM3 GPU 4: NVIDIA H100 80GB HBM3 GPU 5: NVIDIA H100 80GB HBM3 GPU 6: NVIDIA H100 80GB HBM3 GPU 7: NVIDIA H100 80GB HBM3

Nvidia driver version : 570.148.08 cuDNN version : Could not collect HIP runtime version : N/A MIOpen runtime version : N/A Is XNNPACK available : True

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 64 On-line CPU(s) list: 0-63 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 6430 CPU family: 6 Model: 143 Thread(s) per core: 1 Core(s) per socket: 32 Socket(s): 2 Stepping: 8 CPU(s) scaling MHz: 76% CPU max MHz: 3400.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities L1d cache: 3 MiB (64 instances) L1i cache: 2 MiB (64 instances) L2 cache: 128 MiB (64 instances) L3 cache: 120 MiB (2 instances) NUMA node(s): 8 NUMA node0 CPU(s): 0-7 NUMA node1 CPU(s): 8-15 NUMA node2 CPU(s): 16-23 NUMA node3 CPU(s): 24-31 NUMA node4 CPU(s): 32-39 NUMA node5 CPU(s): 40-47 NUMA node6 CPU(s): 48-55 NUMA node7 CPU(s): 56-63 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

============================== Versions of relevant libraries

[pip3] ema-pytorch==0.7.9 [pip3] flashinfer-python==0.6.7 [pip3] helion==0.3.3 [pip3] mypy-extensions==1.1.0 [pip3] numpy==2.2.6 [pip3] nvidia-cublas-cu12==12.9.1.4 [pip3] nvidia-cuda-cupti-cu12==12.9.79 [pip3] nvidia-cuda-nvrtc-cu12==12.9.86 [pip3] nvidia-cuda-runtime-cu12==12.9.79 [pip3] nvidia-cudnn-cu12==9.10.2.21 [pip3] nvidia-cufft-cu12==11.4.1.4 [pip3] nvidia-cufile-cu12==1.14.1.1 [pip3] nvidia-curand-cu12==10.3.10.19 [pip3] nvidia-cusolver-cu12==11.7.5.82 [pip3] nvidia-cusparse-cu12==12.5.10.65 [pip3] nvidia-cusparselt-cu12==0.7.1 [pip3] nvidia-cutlass-dsl==4.4.2 [pip3] nvidia-cutlass-dsl-libs-base==4.4.2 [pip3] nvidia-ml-py==13.595.45 [pip3] nvidia-nccl-cu12==2.27.5 [pip3] nvidia-nvjitlink-cu12==12.9.86 [pip3] nvidia-nvshmem-cu12==3.4.5 [pip3] nvidia-nvtx-cu12==12.9.79 [pip3] onnxruntime==1.24.4 [pip3] pyzmq==27.1.0 [pip3] torch==2.10.0+cu129 [pip3] torchaudio==2.10.0+cu129 [pip3] torchsde==0.2.6 [pip3] torchvision==0.25.0+cu129 [pip3] transformers==5.3.0 [pip3] triton==3.6.0 [pip3] x-transformers==2.17.7 [conda] Could not collect

============================== vLLM Info

ROCM Version : Could not collect vLLM Version : 0.18.1rc1.dev193+497e234d3 (git sha: 497e234d3) vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 NIC4 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 PIX SYS SYS SYS SYS 0-7 0 N/A GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 PXB SYS SYS SYS SYS 0-7 0 N/A GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 SYS PXB NODE SYS SYS 16-23 2 N/A GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 SYS PIX NODE SYS SYS 16-23 2 N/A GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 SYS SYS SYS PXB SYS 32-39 4 N/A GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 SYS SYS SYS PIX SYS 32-39 4 N/A GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 SYS SYS SYS SYS PXB 48-55 6 N/A GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X SYS SYS SYS SYS PIX 48-55 6 N/A NIC0 PIX PXB SYS SYS SYS SYS SYS SYS X SYS SYS SYS SYS NIC1 SYS SYS PXB PIX SYS SYS SYS SYS SYS X NODE SYS SYS NIC2 SYS SYS NODE NODE SYS SYS SYS SYS SYS NODE X SYS SYS NIC3 SYS SYS SYS SYS PXB PIX SYS SYS SYS SYS SYS X SYS NIC4 SYS SYS SYS SYS SYS SYS PXB PIX SYS SYS SYS SYS X

Legend:

X = Self SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI) NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU) PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge) PIX = Connection traversing at most a single PCIe bridge NV# = Connection traversing a bonded set of # NVLinks

NIC Legend:

NIC0: mlx5_0 NIC1: mlx5_1 NIC2: mlx5_2 NIC3: mlx5_3 NIC4: mlx5_4

============================== Environment Variables

NVIDIA_VISIBLE_DEVICES=/var/run/nvidia-container-devices CUDA_COREDUMP_SHOW_PROGRESS=1 VLLM_USE_DEEP_GEMM=1 VLLM_CACHE_ROOT=/tmp/cache/vllm VLLM_LOG_MODEL_INSPECTION=1 CUDA_COREDUMP_GENERATION_FLAGS=skip_nonrelocated_elf_images,skip_global_memory,skip_shared_memory,skip_local_memory,skip_constbank_memory NVIDIA_GDRCOPY=enabled VLLM_FLOAT32_MATMUL_PRECISION=high TORCHINDUCTOR_CACHE_DIR=/tmp/cache/torchinductor_root VLLM_USE_FLASHINFER_SAMPLER=1 CUDA_ENABLE_COREDUMP_ON_EXCEPTION=1 LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/lib/x86_64-linux-gnu:/usr/lib VLLM_NO_USAGE_STATS=1 CUDA_COREDUMP_FILE=/mnt/models/logs/vllm.%h/cuda_coredump_%p.%t VLLM_USE_FLASHINFER_MOE_FP8=0 PYTORCH_NVML_BASED_CUDA_CHECK=1 TORCHINDUCTOR_COMPILE_THREADS=1 VLLM_WORKER_MULTIPROC_METHOD=spawn

Fix Action

Fix / Workaround

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 64 On-line CPU(s) list: 0-63 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 6430 CPU family: 6 Model: 143 Thread(s) per core: 1 Core(s) per socket: 32 Socket(s): 2 Stepping: 8 CPU(s) scaling MHz: 76% CPU max MHz: 3400.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities L1d cache: 3 MiB (64 instances) L1i cache: 2 MiB (64 instances) L2 cache: 128 MiB (64 instances) L3 cache: 120 MiB (2 instances) NUMA node(s): 8 NUMA node0 CPU(s): 0-7 NUMA node1 CPU(s): 8-15 NUMA node2 CPU(s): 16-23 NUMA node3 CPU(s): 24-31 NUMA node4 CPU(s): 32-39 NUMA node5 CPU(s): 40-47 NUMA node6 CPU(s): 48-55 NUMA node7 CPU(s): 56-63 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

PR fix notes

PR #38418: [Bugfix] Disallow renderer_num_workers > 1 with mm processor cache

Description (problem / solution / changelog)

Purpose

Fix a bug where --renderer-num-workers > 1 causes race conditions on the multimodal processor cache, leading to crashes or data corruption.

Neither the LRU nor SHM multimodal processor cache is thread-safe. The renderer's ThreadPoolExecutor dispatches multimodal preprocessing to multiple threads, which concurrently read/write the cache without synchronization. The SHM cache uses a SingleWriterShmRingBuffer that assumes a single writer, and the LRU cache is backed by cachetools.LRUCache which provides no thread-safety guarantees.

This PR adds a config-time validation that raises ValueError when --renderer-num-workers > 1 is used with the cache enabled (--mm-processor-cache-gb > 0), directing users to either keep the default single worker or disable the cache.

Closes #38375

Test Plan

python -m pytest tests/test_config.py::test_renderer_num_workers_with_mm_cache -v

Test Result

Test covers four cases:

  • renderer_num_workers=4 + default cache (gb=4) → raises ValueError

  • renderer_num_workers=2 + explicit cache (gb=1.0) → raises ValueError

  • renderer_num_workers=4 + cache disabled (gb=0) → passes

  • renderer_num_workers=1 + default cache → passes

  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".

  • The test plan, such as providing test command.

  • The test results, such as pasting the results comparison before and after, or e2e results

Changed files

  • tests/test_config.py (modified, +22/-0)
  • vllm/config/model.py (modified, +13/-0)

Code Example

==============================
        System Info
==============================
OS                           : Ubuntu 24.04.3 LTS (x86_64)
GCC version                  : (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.39

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu129
Is debug build               : False
CUDA used to build PyTorch   : 12.9
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.3 (main, Nov  6 2025, 13:44:16) [GCC 13.3.0] (64-bit runtime)
Python platform              : Linux-5.14.0-284.118.1.el9_2.x86_64-x86_64-with-glibc2.39

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 12.9.86
CUDA_MODULE_LOADING set to   : 
GPU models and configuration :
GPU 0: NVIDIA H100 80GB HBM3
GPU 1: NVIDIA H100 80GB HBM3
GPU 2: NVIDIA H100 80GB HBM3
GPU 3: NVIDIA H100 80GB HBM3
GPU 4: NVIDIA H100 80GB HBM3
GPU 5: NVIDIA H100 80GB HBM3
GPU 6: NVIDIA H100 80GB HBM3
GPU 7: NVIDIA H100 80GB HBM3

Nvidia driver version        : 570.148.08
cuDNN version                : Could not collect
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               64
On-line CPU(s) list:                  0-63
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6430
CPU family:                           6
Model:                                143
Thread(s) per core:                   1
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             8
CPU(s) scaling MHz:                   76%
CPU max MHz:                          3400.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
L1d cache:                            3 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             128 MiB (64 instances)
L3 cache:                             120 MiB (2 instances)
NUMA node(s):                         8
NUMA node0 CPU(s):                    0-7
NUMA node1 CPU(s):                    8-15
NUMA node2 CPU(s):                    16-23
NUMA node3 CPU(s):                    24-31
NUMA node4 CPU(s):                    32-39
NUMA node5 CPU(s):                    40-47
NUMA node6 CPU(s):                    48-55
NUMA node7 CPU(s):                    56-63
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] ema-pytorch==0.7.9
[pip3] flashinfer-python==0.6.7
[pip3] helion==0.3.3
[pip3] mypy-extensions==1.1.0
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] onnxruntime==1.24.4
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0+cu129
[pip3] torchaudio==2.10.0+cu129
[pip3] torchsde==0.2.6
[pip3] torchvision==0.25.0+cu129
[pip3] transformers==5.3.0
[pip3] triton==3.6.0
[pip3] x-transformers==2.17.7
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.18.1rc1.dev193+497e234d3 (git sha: 497e234d3)
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    CPU Affinity    NUMA Affinity    GPU NUMA ID
GPU0     X      NV18    NV18    NV18    NV18    NV18    NV18    NV18    PIX     SYS     SYS     SYS     SYS     0-7     0    N/A
GPU1    NV18     X      NV18    NV18    NV18    NV18    NV18    NV18    PXB     SYS     SYS     SYS     SYS     0-7     0    N/A
GPU2    NV18    NV18     X      NV18    NV18    NV18    NV18    NV18    SYS     PXB     NODE    SYS     SYS     16-23   2    N/A
GPU3    NV18    NV18    NV18     X      NV18    NV18    NV18    NV18    SYS     PIX     NODE    SYS     SYS     16-23   2    N/A
GPU4    NV18    NV18    NV18    NV18     X      NV18    NV18    NV18    SYS     SYS     SYS     PXB     SYS     32-39   4    N/A
GPU5    NV18    NV18    NV18    NV18    NV18     X      NV18    NV18    SYS     SYS     SYS     PIX     SYS     32-39   4    N/A
GPU6    NV18    NV18    NV18    NV18    NV18    NV18     X      NV18    SYS     SYS     SYS     SYS     PXB     48-55   6    N/A
GPU7    NV18    NV18    NV18    NV18    NV18    NV18    NV18     X      SYS     SYS     SYS     SYS     PIX     48-55   6    N/A
NIC0    PIX     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      SYS     SYS     SYS     SYS
NIC1    SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS     SYS      X      NODE    SYS     SYS
NIC2    SYS     SYS     NODE    NODE    SYS     SYS     SYS     SYS     SYS     NODE     X      SYS     SYS
NIC3    SYS     SYS     SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS     SYS      X      SYS
NIC4    SYS     SYS     SYS     SYS     SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS      X

Legend:

  X = Self
  SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX = Connection traversing at most a single PCIe bridge
  NV# = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_1
  NIC2: mlx5_2
  NIC3: mlx5_3
  NIC4: mlx5_4

==============================
     Environment Variables
==============================
NVIDIA_VISIBLE_DEVICES=/var/run/nvidia-container-devices
CUDA_COREDUMP_SHOW_PROGRESS=1
VLLM_USE_DEEP_GEMM=1
VLLM_CACHE_ROOT=/tmp/cache/vllm
VLLM_LOG_MODEL_INSPECTION=1
CUDA_COREDUMP_GENERATION_FLAGS=skip_nonrelocated_elf_images,skip_global_memory,skip_shared_memory,skip_local_memory,skip_constbank_memory
NVIDIA_GDRCOPY=enabled
VLLM_FLOAT32_MATMUL_PRECISION=high
TORCHINDUCTOR_CACHE_DIR=/tmp/cache/torchinductor_root
VLLM_USE_FLASHINFER_SAMPLER=1
CUDA_ENABLE_COREDUMP_ON_EXCEPTION=1
LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/lib/x86_64-linux-gnu:/usr/lib
VLLM_NO_USAGE_STATS=1
CUDA_COREDUMP_FILE=/mnt/models/logs/vllm.%h/cuda_coredump_%p.%t
VLLM_USE_FLASHINFER_MOE_FP8=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
VLLM_WORKER_MULTIPROC_METHOD=spawn

---

(APIServer pid=1) INFO 03-28 00:00:07 [async_llm.py:420] Added request chatcmpl-a0fe280d9f2887ae-b8cfa283.
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] WorkerProc hit an exception.
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] Traceback (most recent call last):
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 944, in worker_busy_loop
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     output = func(*args, **kwargs)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]              ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/worker/worker_base.py", line 330, in execute_model
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     self._apply_mm_cache(scheduler_output)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/worker/worker_base.py", line 323, in _apply_mm_cache
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     req_data.mm_features = mm_cache.get_and_update_features(
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/multimodal/cache.py", line 591, in get_and_update_features
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     feature.data = self.get_and_update_item(feature.data, cache_key)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/multimodal/cache.py", line 705, in get_and_update_item
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._shm_cache.get(address, monotonic_id)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/distributed/device_communicators/shm_object_storage.py", line 623, in get
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj = self.ser_de.deserialize(data_view[self.flag_bytes :])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/distributed/device_communicators/shm_object_storage.py", line 396, in deserialize
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj = self.mm_decoder.decode(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 346, in decode
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self.decoder.decode(bufs[0])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 360, in dec_hook
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._decode_mm_item(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 437, in _decode_mm_item
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     {key: self._decode_mm_field_elem(elem) for key, elem in obj.items()}
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 442, in _decode_mm_field_elem
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj["data"] = self._decode_nested_tensors(obj["data"])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 464, in _decode_nested_tensors
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._decode_tensor(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 408, in _decode_tensor
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     buffer = self.aux_buffers[data] if is_aux else data
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]              ~~~~~~~~~~~~~~~~^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] IndexError: list index out of range
...

---

# On a H100 x 8 worker node
vllm serve Qwen/Qwen3-VL-235B-A22B-Instruct \
  --port 8080 \
  --gpu-memory-utilization 0.91 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --max-num-seqs 32 \
  --renderer-num-workers 4 \
  --mm-encoder-tp-mode data \
  --mm-processor-cache-type shm
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
==============================
        System Info
==============================
OS                           : Ubuntu 24.04.3 LTS (x86_64)
GCC version                  : (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.39

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu129
Is debug build               : False
CUDA used to build PyTorch   : 12.9
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.3 (main, Nov  6 2025, 13:44:16) [GCC 13.3.0] (64-bit runtime)
Python platform              : Linux-5.14.0-284.118.1.el9_2.x86_64-x86_64-with-glibc2.39

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 12.9.86
CUDA_MODULE_LOADING set to   : 
GPU models and configuration :
GPU 0: NVIDIA H100 80GB HBM3
GPU 1: NVIDIA H100 80GB HBM3
GPU 2: NVIDIA H100 80GB HBM3
GPU 3: NVIDIA H100 80GB HBM3
GPU 4: NVIDIA H100 80GB HBM3
GPU 5: NVIDIA H100 80GB HBM3
GPU 6: NVIDIA H100 80GB HBM3
GPU 7: NVIDIA H100 80GB HBM3

Nvidia driver version        : 570.148.08
cuDNN version                : Could not collect
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               64
On-line CPU(s) list:                  0-63
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6430
CPU family:                           6
Model:                                143
Thread(s) per core:                   1
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             8
CPU(s) scaling MHz:                   76%
CPU max MHz:                          3400.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
L1d cache:                            3 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             128 MiB (64 instances)
L3 cache:                             120 MiB (2 instances)
NUMA node(s):                         8
NUMA node0 CPU(s):                    0-7
NUMA node1 CPU(s):                    8-15
NUMA node2 CPU(s):                    16-23
NUMA node3 CPU(s):                    24-31
NUMA node4 CPU(s):                    32-39
NUMA node5 CPU(s):                    40-47
NUMA node6 CPU(s):                    48-55
NUMA node7 CPU(s):                    56-63
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] ema-pytorch==0.7.9
[pip3] flashinfer-python==0.6.7
[pip3] helion==0.3.3
[pip3] mypy-extensions==1.1.0
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] onnxruntime==1.24.4
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0+cu129
[pip3] torchaudio==2.10.0+cu129
[pip3] torchsde==0.2.6
[pip3] torchvision==0.25.0+cu129
[pip3] transformers==5.3.0
[pip3] triton==3.6.0
[pip3] x-transformers==2.17.7
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.18.1rc1.dev193+497e234d3 (git sha: 497e234d3)
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    CPU Affinity    NUMA Affinity    GPU NUMA ID
GPU0     X      NV18    NV18    NV18    NV18    NV18    NV18    NV18    PIX     SYS     SYS     SYS     SYS     0-7     0    N/A
GPU1    NV18     X      NV18    NV18    NV18    NV18    NV18    NV18    PXB     SYS     SYS     SYS     SYS     0-7     0    N/A
GPU2    NV18    NV18     X      NV18    NV18    NV18    NV18    NV18    SYS     PXB     NODE    SYS     SYS     16-23   2    N/A
GPU3    NV18    NV18    NV18     X      NV18    NV18    NV18    NV18    SYS     PIX     NODE    SYS     SYS     16-23   2    N/A
GPU4    NV18    NV18    NV18    NV18     X      NV18    NV18    NV18    SYS     SYS     SYS     PXB     SYS     32-39   4    N/A
GPU5    NV18    NV18    NV18    NV18    NV18     X      NV18    NV18    SYS     SYS     SYS     PIX     SYS     32-39   4    N/A
GPU6    NV18    NV18    NV18    NV18    NV18    NV18     X      NV18    SYS     SYS     SYS     SYS     PXB     48-55   6    N/A
GPU7    NV18    NV18    NV18    NV18    NV18    NV18    NV18     X      SYS     SYS     SYS     SYS     PIX     48-55   6    N/A
NIC0    PIX     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      SYS     SYS     SYS     SYS
NIC1    SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS     SYS      X      NODE    SYS     SYS
NIC2    SYS     SYS     NODE    NODE    SYS     SYS     SYS     SYS     SYS     NODE     X      SYS     SYS
NIC3    SYS     SYS     SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS     SYS      X      SYS
NIC4    SYS     SYS     SYS     SYS     SYS     SYS     PXB     PIX     SYS     SYS     SYS     SYS      X

Legend:

  X = Self
  SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX = Connection traversing at most a single PCIe bridge
  NV# = Connection traversing a bonded set of # NVLinks

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_1
  NIC2: mlx5_2
  NIC3: mlx5_3
  NIC4: mlx5_4

==============================
     Environment Variables
==============================
NVIDIA_VISIBLE_DEVICES=/var/run/nvidia-container-devices
CUDA_COREDUMP_SHOW_PROGRESS=1
VLLM_USE_DEEP_GEMM=1
VLLM_CACHE_ROOT=/tmp/cache/vllm
VLLM_LOG_MODEL_INSPECTION=1
CUDA_COREDUMP_GENERATION_FLAGS=skip_nonrelocated_elf_images,skip_global_memory,skip_shared_memory,skip_local_memory,skip_constbank_memory
NVIDIA_GDRCOPY=enabled
VLLM_FLOAT32_MATMUL_PRECISION=high
TORCHINDUCTOR_CACHE_DIR=/tmp/cache/torchinductor_root
VLLM_USE_FLASHINFER_SAMPLER=1
CUDA_ENABLE_COREDUMP_ON_EXCEPTION=1
LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/lib/x86_64-linux-gnu:/usr/lib
VLLM_NO_USAGE_STATS=1
CUDA_COREDUMP_FILE=/mnt/models/logs/vllm.%h/cuda_coredump_%p.%t
VLLM_USE_FLASHINFER_MOE_FP8=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
VLLM_WORKER_MULTIPROC_METHOD=spawn
</details>

🐛 Describe the bug

#34789 introduces renderer threadpool set by --renderer-num-workers CLI argument, but it seems this option is incompatible with --mm-processor-cache-type shm. If we set both options in a vision language model server, it crashes with the following index error under a high concurrency workload (e.g. running chartqa benchmark):

(APIServer pid=1) INFO 03-28 00:00:07 [async_llm.py:420] Added request chatcmpl-a0fe280d9f2887ae-b8cfa283.
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] WorkerProc hit an exception.
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] Traceback (most recent call last):
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 944, in worker_busy_loop
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     output = func(*args, **kwargs)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]              ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/worker/worker_base.py", line 330, in execute_model
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     self._apply_mm_cache(scheduler_output)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/worker/worker_base.py", line 323, in _apply_mm_cache
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     req_data.mm_features = mm_cache.get_and_update_features(
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/multimodal/cache.py", line 591, in get_and_update_features
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     feature.data = self.get_and_update_item(feature.data, cache_key)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/multimodal/cache.py", line 705, in get_and_update_item
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._shm_cache.get(address, monotonic_id)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/distributed/device_communicators/shm_object_storage.py", line 623, in get
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj = self.ser_de.deserialize(data_view[self.flag_bytes :])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/distributed/device_communicators/shm_object_storage.py", line 396, in deserialize
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj = self.mm_decoder.decode(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 346, in decode
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self.decoder.decode(bufs[0])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 360, in dec_hook
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._decode_mm_item(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 437, in _decode_mm_item
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     {key: self._decode_mm_field_elem(elem) for key, elem in obj.items()}
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 442, in _decode_mm_field_elem
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     obj["data"] = self._decode_nested_tensors(obj["data"])
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 464, in _decode_nested_tensors
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     return self._decode_tensor(obj)
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]            ^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]   File "/app/.venv/lib/python3.12/site-packaged/vllm/v1/serial_utils.py", line 408, in _decode_tensor
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]     buffer = self.aux_buffers[data] if is_aux else data
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949]              ~~~~~~~~~~~~~~~~^^^^^^
(Worker_TP7_DCP1_EP7 pid=641) ERROR 03-28 00:00:07 [multiproc_executor.py:949] IndexError: list index out of range
...

example deployment spec

# On a H100 x 8 worker node
vllm serve Qwen/Qwen3-VL-235B-A22B-Instruct \
  --port 8080 \
  --gpu-memory-utilization 0.91 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --max-num-seqs 32 \
  --renderer-num-workers 4 \
  --mm-encoder-tp-mode data \
  --mm-processor-cache-type shm

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extent analysis

Fix Plan

To resolve the IndexError: list index out of range issue when using --renderer-num-workers with --mm-processor-cache-type shm, we need to adjust the shared memory cache handling to accommodate the multi-worker setup.

Here are the steps:

  • Modify the shm_object_storage.py to handle multi-worker access correctly.
  • Implement locking mechanisms to prevent concurrent access issues.
  • Adjust the serial_utils.py to handle tensor decoding in a thread-safe manner.

Code Changes

# In shm_object_storage.py
import threading

class SHMObjectStorage:
    def __init__(self):
        self.lock = threading.Lock()

    def get(self, address, monotonic_id):
        with self.lock:
            # Existing get logic here

    def put(self, address, obj):
        with self.lock:
            # Existing put logic here
# In serial_utils.py
import threading

class SerialUtils:
    def __init__(self):
        self.lock = threading.Lock()

    def _decode_tensor(self, data):
        with self.lock:
            # Existing decode logic here

Verification

To verify the fix, run the deployment spec with the modified code and check for the absence of the IndexError. Monitor the system for any other issues that may arise from the changes.

Extra Tips

  • Ensure that the locking mechanisms are properly implemented to prevent deadlocks.
  • Consider using a more robust caching solution that can handle multi-worker access.
  • Test the changes thoroughly to ensure that they do not introduce any regressions.

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